ldaPrototype - Prototype of Multiple Latent Dirichlet Allocation Runs
Determine a Prototype from a number of runs of Latent Dirichlet Allocation (LDA) measuring its similarities with S-CLOP: A procedure to select the LDA run with highest mean pairwise similarity, which is measured by S-CLOP (Similarity of multiple sets by Clustering with Local Pruning), to all other runs. LDA runs are specified by its assignments leading to estimators for distribution parameters. Repeated runs lead to different results, which we encounter by choosing the most representative LDA run as prototype.
Last updated 2 years ago
latent-dirichlet-allocationldamodel-selectionmodelselectionreliabilitytext-miningtextdatatopic-modeltopic-modelstopic-similaritiestopicmodelingtopicmodelling
4.44 score 8 stars 1 dependents 23 scripts 387 downloadsrollinglda - Construct Consistent Time Series from Textual Data
A rolling version of the Latent Dirichlet Allocation, see Rieger et al. (2021) <doi:10.18653/v1/2021.findings-emnlp.201>. By a sequential approach, it enables the construction of LDA-based time series of topics that are consistent with previous states of LDA models. After an initial modeling, updates can be computed efficiently, allowing for real-time monitoring and detection of events or structural breaks.
Last updated 1 years ago
consistencylatent-dirichlet-allocationldamodel-selectionreliabilitytext-miningtextdatatopic-modeltopic-modelstopicmodeltopicmodelingtopicmodelling
4.03 score 12 stars 18 scripts 306 downloads